Shuo-Huan Hsu

TL;DR: Wang et al. as discussed by the authors derived a dynamic model for roller compaction process based on Johanson's rolling theory, which is used to predict the stress and density profiles during the compaction and the material balance equation which describes the roll gap change.

TL;DR: A novel Bayesian approach to model building is presented that takes advantage of breakthroughs in Monte Carlo sampling procedures and high performance computing to enable high fidelity mathematical modeling.

TL;DR: In this paper, a kinetic model for propane conversion to aromatics was proposed that considers surface species as neutral alkoxides, reactions of these alkoxide species by carbenium ion-like transition states, and alkane activation by carbonium ion like transition states; this model describes the reaction behavior over an HZSM-5 catalyst in terms of relevant rate and equilibrium constants and activation energies.

TL;DR: In this article, the authors demonstrate how online process control can be applied on roller compaction using the simulator built in Part I of this paper, and different control strategies are discussed: multi-loop proportional-integral-derivative, linear model predictive control (MPC), and nonlinear MPC.

TL;DR: The Bayesian approach is used to formulate the model building problem, estimate model parameters by Monte Carlo based methods, discriminate rival models, and design new experiments to improve the discrimination and fidelity of the parameter estimates.